Dynamics of the Ride-Sourcing Market: A Coevolutionary Model of Competition between Two-Sided Mobility Platforms

TL;DR

This paper models the competitive dynamics of two-sided ride-sourcing platforms like Uber and Lyft using a coevolutionary framework, revealing how subsidies and entry timing influence market share and equilibrium outcomes.

Contribution

It introduces a coevolutionary model with S-shaped learning curves to simulate ride-sourcing market dynamics and analyze the effects of subsidies and entry timing on competition.

Findings

Heavy subsidies can sustain new entrants in the market.

Late market entry reduces success chances and may lead to winner-takes-all.

Agent correlation significantly impacts platform market shares.

Abstract

There is a fierce competition between two-sided mobility platforms (e.g., Uber and Lyft) fueled by massive subsidies, yet the underlying dynamics and interactions between the competing plat-forms are largely unknown. These platforms rely on the cross-side network effects to grow, they need to attract agents from both sides to kick-off: travellers are needed for drivers and drivers are needed for travellers. We use our coevolutionary model featured by the S-shaped learning curves to simulate the day-to-day dynamics of the ride-sourcing market at the microscopic level. We run three scenarios to illustrate the possible equilibria in the market. Our results underline how the correlation inside the ride-sourcing nest of the agents choice set significantly affects the plat-forms' market shares. While late entry to the market decreases the chance of platform success and possibly results in "winner-takes-all", heavy subsidies can keep the new platform in competition giving rise to "market sharing" regime.